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Formulation of a novel HRV classification model as a surrogate fraudulence detection schema

Tan, Tian Swee and Kelvin, Ling Chia Hiik and Tan, Jia Hou and Leong, Kah Meng and Abdul-Kadir, Mohammed Rafiq and A. Harris, Arief Ruhullah and Mohd. Rafi, Muhamad Firdaus and Leo, Bodey and Yii, Cheng Tay and Yahya, Azli and Joyce, Sia Sin Yin and Matthias, Tiong Foh Thye and Tengku Alang, Tengku Ahmad Iskandar and Malik, Sameen Ahmed (2020) Formulation of a novel HRV classification model as a surrogate fraudulence detection schema. Malaysian Journal of Fundamental and Applied Sciences, 16 (1). pp. 121-127. ISSN 2289-5981

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Official URL: https://mjfas.utm.my/index.php/mjfas/article/view/...

Abstract

Lie detection has been studied since a few decades ago, usually for the purpose of producing a scheme to assist in the investigation of identifying the culprit from a list of suspects. Heart Rate Variability (HRV) may be used as a method in lie detection due to its versatility and suitability. However, since its analysis is not instantaneous, a new experiment is described in this paper to overcome the problem. Additionally, a preliminary HRV classification model is designed to further enhance the classification model which is able to distinguish the lie from the truth for up to 80%.

Item Type:Article
Uncontrolled Keywords:Heart Rate Variability (HRV), lie detection, classification model
Subjects:Q Science > QH Natural history > QH301 Biology
Divisions:Biosciences and Medical Engineering
ID Code:85579
Deposited By: Fazli Masari
Deposited On:30 Jun 2020 16:53
Last Modified:30 Jun 2020 16:53

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